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Record W2621612651 · doi:10.1159/000475457

Quantification and Dosing of Renal Replacement Therapy in Acute Kidney Injury: A Reappraisal

2017· review· en· W2621612651 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBlood Purification · 2017
Typereview
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsRenal replacement therapyMedicineDosingAcute kidney injuryDialysisRenal functionKidney diseaseMedical prescriptionUrologyIntensive care medicineInternal medicinePharmacology

Abstract

fetched live from OpenAlex

BACKGROUND/AIMS: Delivered dialysis therapy is routinely measured in the management of patients with end-stage renal disease; yet, the quantification of renal replacement prescription and delivery in acute kidney injury (AKI) is less established. While continuous renal replacement therapy (CRRT) is widely understood to have greater solute clearance capabilities relative to intermittent therapies, neither urea nor any other solute is specifically employed for CRRT dose assessments in clinical practice at present. Instead, the normalized effluent rate is the gold standard for CRRT dosing, although this parameter does not provide an accurate estimation of actual solute clearance for different modalities. METHODS: Because this situation has created confusion among clinicians, we reappraise dose prescription and delivery for CRRT. RESULTS: A critical review of RRT quantification in AKI is provided. CONCLUSION: We propose an adaptation of a maintenance dialysis parameter (standard Kt/V) as a benchmark to supplement effluent-based dosing of CRRT. Video Journal Club "Cappuccino with Claudio Ronco" at http://www.karger.com/?doi=475457.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.142
GPT teacher head0.454
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it